The present invention relates to a picture signal coding system for compressing a moving picture signal by progressive coding.
The progressive coding is a method for compressing a picture signal by respectively coding a low frequency component of a little luminance variation and a high frequency component of much luminance variation, both separated from the picture signal. A picture of low resolution is reproduced by decoding the low frequency component thus coded and a picture of high resolution is reproduced by decoding both the low and high frequency components thus coded.
The following is well known in the progressing coding of a moving picture signal. A moving picture signal of an original moving picture is first sub-sampled to produce a low frequency component of a little luminance variation in a present frame. A motion quantity (motion vector) on a decoded low frequency component in a previous frame and the low frequency component is detected.
Motion compensation is conducted using the motion vector to produce a predictive low frequency component. The predictive low frequency component is subtracted from the low frequency component to obtain a predictive error. The predictive error is then subjected to the orthogonal transform and quantization. Quantized transform coefficients and motion vector are then subjected to variable length coding such as the Huffman coding to code the low frequency component.
The quantized transform coefficients and motion vector are further subjected to the inverse orthogonal transform and de-quantization to decode the low frequency component thus coded. The low frequency component thus decoded is over-sampled to produce an over-sampled decoded low frequency component. The over-sampled decoded low frequency component is subtracted from the moving picture signal of the original moving picture to produce a high frequency component of much luminance variation. A motion vector on a decoded high frequency component in a previous frame and the high frequency component in a present frame is detected.
Motion compensation is conducted using the motion vector to produce a predictive high frequency component. The predictive high frequency component is subtracted from the high frequency component to obtain a predictive error. The predictive error is then subjected to the orthogonal transform and quantization. Quantized transform coefficients and motion vector are subjected to variable length coding such as the Huffman coding to code the high frequency component.
A moving picture of low resolution is obtained by decoding the coded low frequency component and the original moving picture is obtained by adding the decoded high frequency component and over-sampled decoded low frequency component.
The above mentioned method has the following disadvantages. A quantization error is produced when the low frequency component is coded and is then coded with the high frequency component. This leads to motion vector detection of low precision on the high frequency component.
Furthermore, motion vectors are respectively detected on the low and high frequency components. This results in the predictive low and high frequency components with no correlation therebetween. Accordingly, when monitored as moving pictures, the low and high frequency components seem to show different actions.
Moreover, both the motion vectors on the low and high frequency components also should be processed in a coding system. This results in an increase in the amount of data to be coded.
There are still further disadvantages. Backward reproduction is sometimes required when magnetic tapes and optical discs are used for example. In this case, the above mentioned progressive coding with the prediction using data in a previous frame cannot conduct decoding because a predictive signal for the decoding cannot be obtained.
Moreover, in communication networks, it sometimes happens that coded data only for a low frequency component is transmitted through limited transmission lines without the following coded data for a high frequency component.